fix: Enhance robustness of issue and quality score processing in the scanner service by adding defensive checks and error handling.
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0735834931
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@ -333,16 +333,13 @@ Please analyze the following code:
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# 尝试从响应中提取JSON
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# 尝试从响应中提取JSON
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result = self._parse_json(content)
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result = self._parse_json(content)
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# 验证和清理结果
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result = self._validate_analysis_result(result)
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# 记录解析后的问题数量
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# 记录解析后的问题数量
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issues_count = len(result.get("issues", []))
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issues_count = len(result.get("issues", []))
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logger.info(f"📊 LLM 分析结果: 发现 {issues_count} 个问题, 质量评分: {result.get('quality_score', 'N/A')}")
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logger.info(f"📊 LLM 分析结果: 发现 {issues_count} 个问题, 质量评分: {result.get('quality_score', 'N/A')}")
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# 检查解析结果是否有效(不是默认响应)
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if result == self._get_default_response():
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error_msg = f"无法解析LLM响应为有效的分析结果 - Provider: {self.config.provider.value}"
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logger.error(error_msg)
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raise Exception(error_msg)
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return result
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return result
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except Exception as e:
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except Exception as e:
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@ -763,6 +760,54 @@ Please analyze the following code:
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raise ValueError(f"json-repair returned unexpected type: {type(repaired)}")
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raise ValueError(f"json-repair returned unexpected type: {type(repaired)}")
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def _validate_analysis_result(self, result: Dict[str, Any]) -> Dict[str, Any]:
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"""验证和清理分析结果"""
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if not isinstance(result, dict):
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logger.warning(f"分析结果不是字典类型: {type(result)}")
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return self._get_default_response()
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# 确保 issues 是列表,且每个元素都是字典
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raw_issues = result.get("issues", [])
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if not isinstance(raw_issues, list):
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logger.warning(f"issues 字段不是列表类型: {type(raw_issues)}")
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raw_issues = []
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valid_issues = []
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for i, issue in enumerate(raw_issues):
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if isinstance(issue, dict):
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valid_issues.append(issue)
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else:
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logger.warning(f"忽略无效的问题格式 (index {i}): {type(issue)}")
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result["issues"] = valid_issues
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# 确保 quality_score 是数字
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score = result.get("quality_score")
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if score is None or not isinstance(score, (int, float)):
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try:
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if score is not None:
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result["quality_score"] = int(float(str(score)))
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else:
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result["quality_score"] = 80
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except (ValueError, TypeError):
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result["quality_score"] = 80
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# 确保 summary 和 metrics 存在
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if "summary" not in result or not isinstance(result["summary"], dict):
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num_issues = len(valid_issues)
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result["summary"] = {
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"total_issues": num_issues,
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"critical_issues": sum(1 for iss in valid_issues if iss.get("severity") == "critical"),
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"high_issues": sum(1 for iss in valid_issues if iss.get("severity") == "high"),
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"medium_issues": sum(1 for iss in valid_issues if iss.get("severity") == "medium"),
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"low_issues": sum(1 for iss in valid_issues if iss.get("severity") == "low")
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}
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if "metrics" not in result or not isinstance(result["metrics"], dict):
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result["metrics"] = self._get_default_response()["metrics"]
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return result
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def _get_default_response(self) -> Dict[str, Any]:
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def _get_default_response(self) -> Dict[str, Any]:
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"""返回默认响应"""
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"""返回默认响应"""
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return {
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return {
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@ -915,6 +960,8 @@ Please analyze the following code:
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raise Exception("LLM返回空响应")
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raise Exception("LLM返回空响应")
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result = self._parse_json(content)
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result = self._parse_json(content)
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# 验证和清理结果
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result = self._validate_analysis_result(result)
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return result
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return result
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except Exception as e:
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except Exception as e:
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@ -680,36 +680,49 @@ async def scan_repo_task(task_id: str, db_session_factory, user_config: dict = N
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# 保存问题
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# 保存问题
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issues = analysis.get("issues", [])
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issues = analysis.get("issues", [])
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for issue in issues:
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for issue in issues:
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line_num = issue.get("line", 1)
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try:
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code_snippet = issue.get("code_snippet")
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# 防御性检查:确保 issue 是字典
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if not code_snippet or len(code_snippet.strip()) < 5:
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if not isinstance(issue, dict):
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try:
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print(f"⚠️ 警告: 任务 {task_id} 中文件 {f_path} 的分析结果包含无效的问题格式: {issue}")
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idx = max(0, int(line_num) - 1)
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continue
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start = max(0, idx - 2)
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end = min(len(file_lines), idx + 3)
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code_snippet = '\n'.join(file_lines[start:end])
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except Exception:
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code_snippet = ""
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audit_issue = AuditIssue(
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line_num = issue.get("line", 1)
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task_id=task.id,
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code_snippet = issue.get("code_snippet")
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file_path=f_path,
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if not code_snippet or len(code_snippet.strip()) < 5:
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line_number=line_num,
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try:
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column_number=issue.get("column"),
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idx = max(0, int(line_num) - 1)
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issue_type=issue.get("type", "maintainability"),
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start = max(0, idx - 2)
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severity=issue.get("severity", "low"),
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end = min(len(file_lines), idx + 3)
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title=issue.get("title", "Issue"),
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code_snippet = '\n'.join(file_lines[start:end])
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message=issue.get("description") or issue.get("title", "Issue"),
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except Exception:
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suggestion=issue.get("suggestion"),
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code_snippet = ""
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code_snippet=code_snippet,
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ai_explanation=issue.get("ai_explanation"),
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audit_issue = AuditIssue(
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status="open"
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task_id=task.id,
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)
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file_path=f_path,
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db.add(audit_issue)
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line_number=line_num,
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total_issues += 1
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column_number=issue.get("column"),
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issue_type=issue.get("type", "maintainability"),
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severity=issue.get("severity", "low"),
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title=issue.get("title", "Issue"),
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message=issue.get("description") or issue.get("title", "Issue"),
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suggestion=issue.get("suggestion"),
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code_snippet=code_snippet,
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ai_explanation=issue.get("ai_explanation"),
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status="open"
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)
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db.add(audit_issue)
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total_issues += 1
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except Exception as e:
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print(f"⚠️ 处理单个问题时出错 (文件 {f_path}): {e}")
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continue
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if "quality_score" in analysis:
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if "quality_score" in analysis:
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quality_scores.append(analysis["quality_score"])
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try:
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quality_score = float(analysis["quality_score"])
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quality_scores.append(quality_score)
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except (ValueError, TypeError):
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pass
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# 更新主任务进度
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# 更新主任务进度
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processed_count = scanned_files + failed_files
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processed_count = scanned_files + failed_files
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